Abstract

Background: Depression is common in patients with coronary artery disease (CAD) and is associated with poorer outcomes and higher costs. Several randomised controlled trials (RCTs) targeting depression, of various modalities (including pharmacological, psychotherapeutic and other approaches), have been conducted and summarised in pairwise meta-analytic reviews. However, no study has considered the cumulative evidence within a network, which can provide valuable indirect comparisons and information about the relative efficacy of interventions. Therefore, we will adopt a review of review methodology to develop a network meta-analysis (NMA) of depression interventions for depression in CAD. Methods: We will search relevant databases from inception for systematic reviews of RCTs of depression treatments for people with CAD, supplementing this with comprehensive searches for recent or ongoing studies. We will extract data from and summarise characteristics of individual RCTs, including participants, study characteristics, outcome measures and adverse events. Cochrane risk of bias ratings will also be extracted or if not present will be conducted by the authors. RCTs that compare depression treatments (grouped as pharmacological, psychotherapeutic, combined pharmacological/psychotherapeutic, exercise, collaborative care) to placebo, usual care, waitlist control or attention controls, or directly in head-to-head comparisons, will be included. Primary outcomes will be the change in depressive symptoms (summarised with a standardised mean difference) and treatment acceptability (treatment discontinuation: % of people who withdrew). Secondary outcomes will include change in 6-month depression outcomes, health-related quality of life (HRQoL), mortality, cardiovascular morbidity, health services use and adverse events. Secondary analyses will form further networks with individual anti-depressants and psychotherapies. We will use frequentist, random effects multivariate network meta-analysis to synthesise the evidence for depression intervention and to achieve a ranking of treatments, using Stata. Rankograms and surface under the cumulative ranking curves will be used for treatment ranking. Local and global methods will evaluate consistency. GRADE will be used to assess evidence quality for primary outcomes. Discussion: The present review will address uncertainties about the evidence in terms of depression management in CAD and may allow for a ranking of treatments, including providing important information for future research efforts.

abstract = "Background: Depression is common in patients with coronary artery disease (CAD) and is associated with poorer outcomes and higher costs. Several randomised controlled trials (RCTs) targeting depression, of various modalities (including pharmacological, psychotherapeutic and other approaches), have been conducted and summarised in pairwise meta-analytic reviews. However, no study has considered the cumulative evidence within a network, which can provide valuable indirect comparisons and information about the relative efficacy of interventions. Therefore, we will adopt a review of review methodology to develop a network meta-analysis (NMA) of depression interventions for depression in CAD. Methods: We will search relevant databases from inception for systematic reviews of RCTs of depression treatments for people with CAD, supplementing this with comprehensive searches for recent or ongoing studies. We will extract data from and summarise characteristics of individual RCTs, including participants, study characteristics, outcome measures and adverse events. Cochrane risk of bias ratings will also be extracted or if not present will be conducted by the authors. RCTs that compare depression treatments (grouped as pharmacological, psychotherapeutic, combined pharmacological/psychotherapeutic, exercise, collaborative care) to placebo, usual care, waitlist control or attention controls, or directly in head-to-head comparisons, will be included. Primary outcomes will be the change in depressive symptoms (summarised with a standardised mean difference) and treatment acceptability (treatment discontinuation: % of people who withdrew). Secondary outcomes will include change in 6-month depression outcomes, health-related quality of life (HRQoL), mortality, cardiovascular morbidity, health services use and adverse events. Secondary analyses will form further networks with individual anti-depressants and psychotherapies. We will use frequentist, random effects multivariate network meta-analysis to synthesise the evidence for depression intervention and to achieve a ranking of treatments, using Stata. Rankograms and surface under the cumulative ranking curves will be used for treatment ranking. Local and global methods will evaluate consistency. GRADE will be used to assess evidence quality for primary outcomes. Discussion: The present review will address uncertainties about the evidence in terms of depression management in CAD and may allow for a ranking of treatments, including providing important information for future research efforts.",

N2 - Background: Depression is common in patients with coronary artery disease (CAD) and is associated with poorer outcomes and higher costs. Several randomised controlled trials (RCTs) targeting depression, of various modalities (including pharmacological, psychotherapeutic and other approaches), have been conducted and summarised in pairwise meta-analytic reviews. However, no study has considered the cumulative evidence within a network, which can provide valuable indirect comparisons and information about the relative efficacy of interventions. Therefore, we will adopt a review of review methodology to develop a network meta-analysis (NMA) of depression interventions for depression in CAD. Methods: We will search relevant databases from inception for systematic reviews of RCTs of depression treatments for people with CAD, supplementing this with comprehensive searches for recent or ongoing studies. We will extract data from and summarise characteristics of individual RCTs, including participants, study characteristics, outcome measures and adverse events. Cochrane risk of bias ratings will also be extracted or if not present will be conducted by the authors. RCTs that compare depression treatments (grouped as pharmacological, psychotherapeutic, combined pharmacological/psychotherapeutic, exercise, collaborative care) to placebo, usual care, waitlist control or attention controls, or directly in head-to-head comparisons, will be included. Primary outcomes will be the change in depressive symptoms (summarised with a standardised mean difference) and treatment acceptability (treatment discontinuation: % of people who withdrew). Secondary outcomes will include change in 6-month depression outcomes, health-related quality of life (HRQoL), mortality, cardiovascular morbidity, health services use and adverse events. Secondary analyses will form further networks with individual anti-depressants and psychotherapies. We will use frequentist, random effects multivariate network meta-analysis to synthesise the evidence for depression intervention and to achieve a ranking of treatments, using Stata. Rankograms and surface under the cumulative ranking curves will be used for treatment ranking. Local and global methods will evaluate consistency. GRADE will be used to assess evidence quality for primary outcomes. Discussion: The present review will address uncertainties about the evidence in terms of depression management in CAD and may allow for a ranking of treatments, including providing important information for future research efforts.

AB - Background: Depression is common in patients with coronary artery disease (CAD) and is associated with poorer outcomes and higher costs. Several randomised controlled trials (RCTs) targeting depression, of various modalities (including pharmacological, psychotherapeutic and other approaches), have been conducted and summarised in pairwise meta-analytic reviews. However, no study has considered the cumulative evidence within a network, which can provide valuable indirect comparisons and information about the relative efficacy of interventions. Therefore, we will adopt a review of review methodology to develop a network meta-analysis (NMA) of depression interventions for depression in CAD. Methods: We will search relevant databases from inception for systematic reviews of RCTs of depression treatments for people with CAD, supplementing this with comprehensive searches for recent or ongoing studies. We will extract data from and summarise characteristics of individual RCTs, including participants, study characteristics, outcome measures and adverse events. Cochrane risk of bias ratings will also be extracted or if not present will be conducted by the authors. RCTs that compare depression treatments (grouped as pharmacological, psychotherapeutic, combined pharmacological/psychotherapeutic, exercise, collaborative care) to placebo, usual care, waitlist control or attention controls, or directly in head-to-head comparisons, will be included. Primary outcomes will be the change in depressive symptoms (summarised with a standardised mean difference) and treatment acceptability (treatment discontinuation: % of people who withdrew). Secondary outcomes will include change in 6-month depression outcomes, health-related quality of life (HRQoL), mortality, cardiovascular morbidity, health services use and adverse events. Secondary analyses will form further networks with individual anti-depressants and psychotherapies. We will use frequentist, random effects multivariate network meta-analysis to synthesise the evidence for depression intervention and to achieve a ranking of treatments, using Stata. Rankograms and surface under the cumulative ranking curves will be used for treatment ranking. Local and global methods will evaluate consistency. GRADE will be used to assess evidence quality for primary outcomes. Discussion: The present review will address uncertainties about the evidence in terms of depression management in CAD and may allow for a ranking of treatments, including providing important information for future research efforts.